Top 18 Business Analytics Tools Used by Companies Today

By | July 30, 2023

In today’s data-driven landscape, businesses rely heavily on vast data for success. However, many companies struggle to analyze this abundance of data effectively. That’s where business analytics comes into the picture. 

Data-driven organizations often employ Business Analysts to help them make informed decisions and gain valuable insights from historical data. Business analytics empowers companies to become more efficient, optimize processes, automate tasks, and focus on revenue growth.

One crucial aspect of Business Analytics is its ability to help organizations comprehend short- and long-term risks using data such as customer preferences and trends. By delving into this data, organizations can understand the reasons behind specific outcomes, reduce risks, improve business processes and solutions, and predict the likelihood of certain results. Business Analytics is a guiding force, providing valuable insights that help businesses thrive in the modern data-driven world.

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Top Business Analytics Tools

 

1.QlikView:

QlikView, developed by Qlik, is a highly recommended tool for business analytics. It stands out for its quick response time compared to Tableau. It makes data analysis easy by associating and identifying relevant data. No programming knowledge is required to use QlikView, although understanding SQL and VB Script can be helpful. Qlik supports disseminating its technology by providing a free version for personal use, making it ideal for small businesses and individual learners.

2. Altair:

Altair offers an open, scalable, unified data analytics platform with integrated data transformation and predictive analytics tools. Altair Monarch provides desktop-based data preparation, while Knowledge Hub offers team-driven data preparation and a centralized data marketplace for collaboration and control. Predictive analytics and machine learning are available within Knowledge Studio, and Altair Panopticon houses streaming processing and real-time visualization capabilities.

3.AnswerRocket:

AnswerRocket provides a data analytics platform powered by search, catering to business users. It allows users to ask business-related questions in everyday language and generate reports and analyses without technical expertise. The platform combines AI and machine learning with powerful analytical capabilities. Native voice recognition and mobile-friendliness are added benefits, and AnswerRocket can automate tasks and answer ad hoc inquiries.

4. Board:

Board is a market-leading business analytics approach that enables users to build interactive and understandable reports and dashboards. It integrates powerful statistical tools into a highly scalable analytics platform. The tool can handle vast amounts of data and provides accurate scenario analysis and forecasting by modifying the data for scenarios.

5. MicroStrategy:

MicroStrategy offers a business analytics platform with excellent analytics capabilities for efficiently analyzing unstructured text data. It includes text analytics software to examine unstructured data further. Users can fetch additional data sources for analysis, and the platform supports data discovery, visualizations, flat files, and web services. A fundamental understanding of programming, data analysis, and SQL is necessary for its usage.

6. TIBCO Spotfire:

TIBCO Spotfire is an advanced business analytics tool providing robust and automated solutions for business reports and analyses. It offers scalability, statistical analysis tools, and the ability to analyze text-based unstructured data. The recent platform upgrade enhances its capabilities further.

7. Sisense:

Sisense is a well-known business analytics tool with powerful text analytics capabilities to transform unstructured text into crucial business insights. It incorporates open-source language for computational statistics and Sisense Crowd Accelerated BI. It enables users to analyze in-depth and comprehend complex visualizations for data-driven decision-making and pattern recognition.

8. KNIME:

KNIME is a user-friendly, open-source business analytics platform that enables users to access, combine, analyze, and visualize data without the need for programming. Its no-code interface makes it perfect for analytics beginners, while experienced professionals can harness its advanced data science tools. KNIME supports various structured and unstructured data types, including PDFs, CSVs, XLS, XML text formats, time series data, spreadsheets, and more.

9.RapidMiner:

RapidMiner is a popular platform for business analytics and data science. It empowers professionals to perform predictive analysis and advanced analytics, such as machine learning, data mining, and data visualization, all without requiring coding experience. RapidMiner supports a wide range of data sources, including Excel, Access, Tera Data, IBM SPSS, Oracle, and more, giving you control over datasets and formats for predictive analysis.

10. Apache Spark:

Apache Spark is another open-source platform that excels at analyzing unstructured data. It easily integrates with other data ecosystems like Hadoop, making it a popular choice. With its machine-learning library, Apache Spark is a fantastic option for business analytics.

11. R Programming:

R is an open-source programming language known for graphics and statistical computing, widely used in business analytics. It aids in data mining and statistical analysis, enabling professionals to build practical models and identify patterns in data. Knowledge of R programming is essential for a career in business analytics.

12. Python:

Python is the most sought-after programming language in the business analytics field, especially with the growing importance of Big Data. Python seamlessly integrates with big data and has become even more valuable in developing analytical and statistical libraries like SciPy and NumPy. Its simplicity and versatility make it a favorite among programmers.

13. Dundas BI:

Dundas BI is a flexible open-source platform for business analytics, allowing professionals to create and view interactive reports, dashboards, scorecards, and more. It handles large volumes of complex data, including text and location-based data, ensuring no data points are left behind.

14. Apache Storm:

Apache Storm is a real-time data processing system designed to handle massive amounts of data in a horizontally scalable and fault-tolerant manner. It’s specifically suited for processing real-time data, making it an excellent choice for stream processing.

15. PIG & HIVE:

As integral components of the Hadoop ecosystem, Pig and Hive simplify MapReduce queries, reducing user complexity. While Pig is commonly used for semi-structured data by programmers and researchers, Hive is favored by analytics professionals for fully structured data.

16. MS Excel:

Microsoft Excel is one of the most popular and cost-effective business analytics tools globally. Its user-friendly interface and widespread accessibility make it a preferred choice for many organizations over more advanced software like SAS and Tableau. 

Excel boasts powerful features, including data summarisation, flexible data filtering, form creation, and Pivot Tables. It can handle small and massive datasets, making it suitable for various data types.

17. MS Power BI:

Another favored business analytics tool from Microsoft is Power BI. This tool focuses on data visualization, enabling professionals to build interactive reports and gain valuable insights. It also offers data warehousing capabilities like data discovery and preparation. 

With Power BI, users can spot real-time trends in data and easily share reports. The package includes Power BI Desktop for desktop-based usage and Power BI Services for cloud-based access, ensuring convenience from anywhere.

19. SAS:

SAS stands as a statistical software renowned for its prowess in data management, predictive analysis, and advanced analytics. Analytics professionals widely utilize SAS due to its straightforward methodologies and ability to handle large datasets. With SAS, users can transform raw data into valuable information in real-time, simplifying complex analysis. The platform facilitates sharing visuals and reports with team members via the web and mobile devices, enhancing collaboration.

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Frequently Asked Questions

Q1. Which business analytics tool is the most popular and widely used? 

Ans. Splunk is a commonly used tool for analytics in small and medium-sized industries. Initially designed for processing machine log file data, it has evolved with time to include advanced features and a user-friendly interface.

Q2. What are the most common tools used for analyzing a company? 

Ans. Some of the best analytical tools for business analysis include 

  • SWOT analysis
  • PEST analysis 
  • Microsoft Power BI 
  • MOST analysis
  • Heptalysis, de Bono’s Six Thinking Hats, CATWOE, Five Whys, MoSCoW, SCRS, and VPEC-T.

Q3. Can you suggest some effective tools for business analytics?

Ans. The list includes Excel, SAS, Microsoft Power BI, Tableau, Qlik Sense, Splunk, and MicroStrategy.

Q4. Mention 5 categories of analytics tools. 

Ans. There are 5 categories of analytics tools: descriptive, diagnostic, predictive, prescriptive, and cognitive. They can be used separately or in combination.

Q5. What are the three fundamental analysis tools? 

Ans. To analyze financial statements, the three primary tools are horizontal analysis, vertical analysis, and ratio analysis.

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